Johann Brehmer, Kyle Cranmer, Gilles Louppe, and Juan Pavez

• cluster_scripts: SLURM scripts that start the preprocessing and experiments on the NYU HPC cluster.
• data: The data set, including both the original weighted event sample as well as the unweighted training, calibration, and evaluation samples. Some of these are quite large and not on GitHub.
• evaluation: IPython notebooks that extract metrics and figures from the experiments.
• figures: Here the figures are stored.
• higgs_inference: The main folder for the inference experiments.
  • models: The keras model code at the heart of many inference strategies.
  • strategies: Training and evaluation routines for the different inference strategies.
  • various: Different utility functions.
  • experiments.py: Main executable that starts the different training and evaluation pieces.
  • settings.py: Most settings and constants, including the main directories, event numbers, architecture parameters, and benchmark thetas.
• preprocessing: Unweighting routines that generate the different training, calibration, and evaluation samples from the original weighted event file.
• postprocessing: Code for the Neyman construction.
• prototypes: Toy experiments and cross-checks on other data. Includes the flow folder with a PyTorch implementation of normalizing flows.
• results: The predictions of the different algorithms on the test data set.